> Markdown version of [/jobs/ext/1441516-senior-ai-engineer](https://www.wearedevelopers.com/jobs/ext/1441516-senior-ai-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior AI Engineer - **Company:** Brown Brothers Harriman & Co. - **Location:** Boston, MA, United States - **Experience:** Expert - **Salary:** $175,000.0 - $215,000.0 - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Microsoft Azure, Software Quality, Code Review, Information Engineering, Extract Transform Load (ETL), Data Transformation, Python (Programming Language), Open Source Technology, Software Engineering, Large Language Models, Prompt Engineering, Backend - **Published:** July 25, 2026 - **Apply:** https://bbh.wd5.myworkdayjobs.com/BBH/job/Boston/Senior-AI-Engineer_72160 ## About the Role * 5+ years software engineering; 1+ years focused on GenAI/LLM applications in production * Has shipped AI features to real users - not just prototypes or internal demos Technical Skills * Hands-on with LLM APIs in production - Anthropic Claude and/or OpenAI * Built and shipped RAG systems to production (not just experimented with them) * Experience with agentic frameworks - Agno, LangChain, LlamaIndex, or comparable * Strong Python proficiency * Azure or AWS cloud experience * Vector databases - Pinecone, Weaviate, pgvector, or comparable * Active user of AI coding assistants in daily workflow Nice to Have * Financial services or data domain background - understanding of financial data schemas, transformation logic, or data quality requirements adds significant context to the role * Experience with Temporal or workflow orchestration systems * Experience fine-tuning models or working with open-source LLMs for domain-specific tasks * Open-source AI contributions or technical writing * Data engineering familiarity - understanding ETL/ELT patterns helps in building more effective transformation generation features ## Description As an AI Engineer, you'll build the intelligence layer of the platform - the AI-powered features that allow financial services users to generate data transformations from natural language, get intelligent integration suggestions, detect data quality issues, and refine outputs based on feedback. This is where the product stops feeling like a tool and starts feeling genuinely new. This is a hands-on production role. You'll build and iterate on LLM pipelines, RAG systems, and agentic workflows using Agno; optimize AI systems for accuracy, latency, and cost in a context where correctness matters; and collaborate closely with Backend Engineers to ensure AI capabilities are reliably surfaced through the platform. You'll work under the direction of the Head of AI Engineering and have real ownership over the features you build. Responsibilities AI Feature Development * Build and iterate on AI-powered product features - transformation generation from natural language, integration configuration suggestions, data quality detection, and automated validation * Implement LLM pipelines that are robust, observable, and production-ready - not proof-of-concepts LLM Pipeline Engineering * Build and optimize LLM pipelines including prompt engineering, context management, and RAG systems tailored to financial services data schemas * Evaluate and improve AI output quality continuously - build evaluation datasets and automated scoring frameworks * Optimize for accuracy, latency, and cost across different usage patterns Agentic Workflows * Implement multi-step agentic workflows using Agno, * Build workflows that handle complex, multi-turn AI interactions cleanly - with proper error handling, retry logic, and human escalation paths Platform Collaboration * Work closely with Backend Engineers to integrate AI capabilities into the platform's API and workflow layer * Build the service interfaces that connect AI outputs to platform execution cleanly * Participate in code reviews and maintain high standards for code quality and testability ## Related Videos - [Developing the Backend with Stefan Lingler, CTO at Shpock](https://www.wearedevelopers.com/videos/100360-developing-the-backend-with-stefan-lingler-cto-at-shpock) - [Are Code Reviews Worth It? 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